Half-century evidence from western Canada shows forest dynamics are primarily driven by competition followed by climate
Bibliographic record
Abstract
Tree mortality, growth, and recruitment are essential components of forest dynamics and resiliency, for which there is great concern as climate change progresses at high latitudes. Tree mortality has been observed to increase over the past decades in many regions, but the causes of this increase are not well understood, and we know even less about long-term changes in growth and recruitment rates. Using a dataset of long-term (1958-2009) observations on 1,680 permanent sample plots from undisturbed natural forests in western Canada, we found that tree demographic rates have changed markedly over the last five decades. We observed a widespread, significant increase in tree mortality, a significant decrease in tree growth, and a similar but weaker trend of decreasing recruitment. However, these changes varied widely across tree size, forest age, ecozones, and species. We found that competition was the primary factor causing the long-term changes in tree mortality, growth, and recruitment. Regional climate had a weaker yet still significant effect on tree mortality, but little effect on tree growth and recruitment. This finding suggests that internal community-level processes-more so than external climatic factors-are driving forest dynamics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".